The group of Prof. Rasulev is focused on development of artificial intelligence (AI)-based predictive models to design novel polymeric materials, nanomaterials and to predict their various properties, including toxicity, solubility, fouling release properties, elasticity, degradation rate, biodegradation, etc. The group applies computational chemistry, machine learning and cheminformatics methods for modeling, data analysis and development of predictive structure-property relationship models to find structural factors responsible for activity of investigated materials.
Prof. Bakhtiyor Rasulev is an Associate Professor in Department of Coatings and Polymeric Materials (CPM); Affiliate faculty in Materials and Nanotechnology (MNT) Program and Biomedical Engineering (BME) Program.
The Rasulev group is also involved in development of methods to encode complex materials (multi-component materials, multi-layered materials, nanomaterials, polymeric materials) for application in machine learning models development to predict materials properties, as well as development of a materials database, which will be useful in designing new polymeric materials, nanomaterials and hybrid/composite materials, as well as assist in prediction of various physico-chemical properties, biological activity, including toxicity and degradation pathways for life cycle assessment.
